Thin-Slice Magnetic Resonance Imaging-Based Radiomics Signature Predicts Chromosomal 1p/19q Co-deletion Status in Grade II and III Gliomas

Ziren Kong; Chendan Jiang; Yiwei Zhang; Sirui Liu; Delin Liu; Zeyu Liu; Wenlin Chen; Penghao Liu; Tianrui Yang; Yuelei Lyu; Dachun Zhao; Hui You; Yu Wang; Wenbin Ma; Feng Feng

doi:10.3389/fneur.2020.551771

Thin-Slice Magnetic Resonance Imaging-Based Radiomics Signature Predicts Chromosomal 1p/19q Co-deletion Status in Grade II and III Gliomas

Front Neurol. 2020 Oct 22:11:551771. doi: 10.3389/fneur.2020.551771. eCollection 2020.

Authors

Ziren Kong¹, Chendan Jiang¹, Yiwei Zhang², Sirui Liu², Delin Liu¹, Zeyu Liu², Wenlin Chen¹, Penghao Liu¹, Tianrui Yang¹, Yuelei Lyu^{2

3}, Dachun Zhao⁴, Hui You², Yu Wang¹, Wenbin Ma¹, Feng Feng²

Affiliations

¹ Department of Neurosurgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
² Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
³ Department of Radiology, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China.
⁴ Department of Pathology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.

Abstract

Objective: Chromosomal 1p/19q co-deletion is recognized as a diagnostic, prognostic, and predictive biomarker in lower grade glioma (LGG). This study aims to construct a radiomics signature to non-invasively predict the 1p/19q co-deletion status in LGG. Methods: Ninety-six patients with pathology-confirmed LGG were retrospectively included and randomly assigned into training (n = 78) and validation (n = 18) dataset. Three-dimensional contrast-enhanced T1 (3D-CE-T1)-weighted magnetic resonance (MR) images and T2-weighted MR images were acquired, and simulated-conventional contrast-enhanced T1 (SC-CE-T1)-weighted images were generated. One hundred and seven shape, first-order, and texture radiomics features were extracted from each imaging modality and selected using the least absolute shrinkage and selection operator on the training dataset. A 3D-radiomics signature based on 3D-CE-T1 and T2-weighted features and a simulated-conventional (SC) radiomics signature based on SC-CE-T1 and T2-weighted features were established using random forest. The radiomics signatures were validated independently and evaluated using receiver operating characteristic (ROC) curves. Tumors with IDH mutations were also separately assessed. Results: Four radiomics features were selected to construct the 3D-radiomics signature and displayed accuracies of 0.897 and 0.833, areas under the ROC curves (AUCs) of 0.940 and 0.889 in the training and validation datasets, respectively. The SC-radiomics signature was constructed with 4 features, but the AUC values were lower than that of the 3D signature. In the IDH-mutated subgroup, the 3D-radiomics signature presented AUCs of 0.950-1.000. Conclusions: The MRI-based radiomics signature can differentiate 1p/19q co-deletion status in LGG with or without predetermined IDH status. 3D-CE-T1-weighted radiomics features are more favorable than SC-CE-T1-weighted features in the establishment of radiomics signatures.

Keywords: MRI; chromosomal 1p/19q co-deletion; glioma; radiomic; spacing.